Sandeep Sambhaji Udmale

Veermata Jijabai Technological Institute | VJTI · Computer Engineering and Information Technology

Intelligent identification of license plates (LPs) is essential for developing efficient and secure transportation systems. However, recognizing LPs can present a significant challenge given the numerous camera angles, lighting situations, and backgrounds. This research suggests a sequence recognition method for identifying LPs to overcome these di...

This work addresses the rolling element bearing (REB) fault classification problem by tackling the issue of identifying the appropriate parameters for the extreme learning machine (ELM) and enhancing its effectiveness. This study introduces a memetic algorithm (MA) to identify the optimal ELM parameter set for compact ELM architecture alongside bet...

Seizure prediction from electroencephalogram (EEG) time series data and a sequential deep learning (DL) predictor substantially boosts epileptic patients’ quality of life. However, a significant challenge is a variation in seizure characteristics with time and individuals along with a need for more data. Also, considerable dissimilarity is noticed...

Deep learning techniques can form generalized models that can solve any problem that is not solvable by traditional approaches. It explains the omnipresence of deep learning models across all domains. However, a lot of time is spent on finding the optimal hyperparameters to help the model generalize and give the highest accuracy. This paper investi...

Most existing Automatic License Plate Recognition (ALPR) approaches focus on images containing approximately frontal views. The considerable variation of LP across complicated environments and perspectives remains a massive challenge for a robust ALPR. This work proposes a comprehensive ALPR paradigm emphasizing unrestricted express screenplays in...

Epilepsy is a major threat to society regarding the treatment time, cost, and unpredictable nature of the disease, imposing an urgent need for intelligent analysis. Electroencephalogram (EEG) is a commonly deployed test for detecting epilepsy that analyses the electrical activity of an individual's brain. In this work, an optimized deep sequential...

Verifying image authentication is necessary when images support evidence for essential purposes such as law enforcement and forensic investigation. The self-embedding fragile watermarking method is a powerful technique for confirming exact content authentication and restoration. This paper proposes the integer wavelet transform(IWT) based watermark...

A self-embedding block-wise fragile image watermarking scheme is proposed in this paper for authentication, localization, and recovery with enhanced accuracy. In this introduced scheme, the cover image is split into non-overlapping blocks with a size of 2 × 2, and each block, ten restoration bits and two authentication bits are calculated from the...

The intelligent supervision of the industrial system is achieved through Industry 4.0. Thus, artificial intelligent-based approaches are widely constructed by incorporating the latest signal processing and sensor technologies to maintain mechanical equipment health and safety during operations. The advancement in technology has introduced multiple...

Livestock management involves the monitoring of farm animals by tracking certain physiological and phenotypical characteristics over time. In the dairy industry, for instance, cattle are typically equipped with RFID ear tags. The corresponding data (e.g. milk properties) can then be automatically assigned to the respective cow when they enter the m...

Agricultural automation is an emerging subject today to accomplish the food demands of individuals across the globe. Machine learning is one such agricultural automation tool that has been adopted briskly in the recent decade due to its ability to process countless input data and handle non‐linear tasks. Availability and continuous development of a...

Hate Speech is an expression that expresses hatred towards people of a specific ethnic group or nationality and incites hatred. Even though many countries have anti-hate speech legislation, hate speech can spread in the native language on social media platforms, resulting in violent riots and protests that spiral out of control and result in anti-s...

Despite attention models’ (AM) success in diverse domains, their application in failure detection and predictive maintenance (FDPM) field is limited. The existing literature of complex rotating machinery (RM) systems with multiple sensors pose the following challenges in applying AM and transformer networks: i) lack of proper fault-specific embeddi...

Hate speech is about making insults or stereotypes towards a person or a group of people based on its characteristics such as origin, race, gender, religion, and more. Thus, hate speech can be classified using machine learning and deep learning methods, and it gives a distinguished output from one class to another. Also, every day tons of data are...

The advancement in sensing technology has enabled the development of various applications for activity recognition using smartphone sensor data. One of the useful applications in an intelligent transportation system is the identification of transportation mode to provide context-aware assistance for the execution of systems such as driver assistant...

In modern times, every device runs on electricity. Batteries are fulfilling electricity needs for portable devices. In all the latest portable electronic devices, lithium-ion batteries (LIBs) are the primary source of power: the reason being their high charge storage density. The primary issue with the LIB is the lack of information on its remainin...

Rotating machinery (RM) fault diagnosis based on artificial intelligence (AI) is an esteemed industrial IoT application and an inevitable constituent of the Industry 4.0 revolution. Notably, the existing research in this area exhibits the following limitations: i) the time-series characterization or system dynamics considerations of vibration input...

Artificial intelligence (AI)-based rotor fault diagnosis (RFD) poses a variety of challenges to the prognostics and health management (PHM) of the Industry 4.0 revolution. Rotor faults have drawn more attention from the AI research community in terms of utilizing fault-specific characteristics in its feature engineering, compared to any other rotat...

Artificial intelligence (AI) based rotating machinery fault diagnosis has extreme importance in the industrial automation and control systems since rotating machinery constitutes approximately 40% of the overall machinery in the industry. But, the majority of AI-based solutions in rotor faults diagnosis are in an experimental stage due to i) inadeq...

Health is a major concern for everyone in today’s world. The number of health problems faced by people today is increasing, and largely regardless of their age. Identification of health-related issues can assist in finding a cure as early as possible and can also lead to a better quality of life. The traditional healthcare system is comparatively m...

Among the variety of applications enabled by the Internet of Things (IoT), healthcare is the most attractive and vital. A lot (volume) of different types (variety) of health data are captured in real time (velocity) by the network of sensors either put on the body or placed in living environments while maintaining the correctness (veracity) of data...

Extensive research has helped to make the extraordinary progress in multiple technologies and as an effect it has strengthened the existing medical services. Specifically, the introduction of the Internet of things (IoT) in the healthcare industry has shown promising results by connecting the various medical resources for efficient utilization. Thu...

Data analytics is the soul of the internet of things (IoT) technology. This is because the use of IoT is beneficial only if the data collected by millions of sensors can be interpreted in some way. In this chapter, we discuss some state-of-the-art techniques used to analyze an individual's health-related data collected by various IoT devices. We al...

Internet of things (IoT) has been taking the industrial sector by storm. Healthcare is one such field that has begun to realize its utility. The health insurance companies which form a small but significant part of the healthcare ecosystem have also begun using this technology to adapt their service models. This chapter discusses various ways in wh...

This article focuses on identifying tiny faces in thermal images using transfer learning. Although the issue of identifying faces in images is not new, the problem of tiny face identification is a recently identified research area. Indeed challenging, however, in this paper, we take the problem one step ahead and focus on recognizing tiny faces in...

Today’s industry demands precise functioning and zero failure of rotating machinery (RM) to avoid disastrous accidents as well as financial losses. Rolling element bearings (REBs) are the heart of RM. Therefore, as early as possible to provide the significant time for maintenance planning, an intelligent diagnosis of REB fault is a critical and cha...

The development of sensor technology and modern computing allows the fault diagnosis of rotating machinery to exploit under different working conditions. As an effect, digital health monitoring of machine is performed based on the actual data values obtained from the multi-sensor, and also, it supports to design the data-rich datasets using multi-s...

Today’s modern industry has widely accepted the intelligent condition monitoring system to improve the industrial organization. As an effect, the data-driven-based fault diagnosis methods are designed by integrating signal processing techniques along with artificial intelligence methods. Various signal processing approaches have been proposed for f...

Today’s modern industry has accepted condition monitoring based on intelligent fault diagnosis of rotating machinery systems to provide precision and sustainability. The conventional signal processing methods are less productive due to the involvement of various noises from different sources in the vibration signal, and therefore, recently fault di...

The condition monitoring of rotating machinery has been widely accepted by the industrial system for intelligent fault diagnosis to achieve sustainability, high performance and provide safety to workers. Therefore, in recent years, artificial intelligence (AI) and signal processing (SP) methods are operated collectively for fault diagnosis. The com...

The condition monitoring of rotating machinery systems based on effective and intelligent fault diagnosis has been widely accepted. Traditional signal processing (SP) methods are less effective due to noises and interferences from different sources and incipient faults which remain active for a short time with a particular frequency. In recent time...

The most common application of graph theory is search problems. Using graph theory, this project aims to solve one such NP-hard problem, i.e., finding a path for a Rubik’s cube to reach the solved state from a scrambled one. Rubik’s cube is among one of the fascinating puzzles and solving them has been a challenge given its vast search space of 43...

Recommender system is the backbone of e-commerce marketing strategies. Popular e-commerce websites use techniques like memory-based collaborative filtering approach based on user similarity with only rank as an attribute. This paper proposes a model-based collaborative filtering recommender system based on probabilistic model using improved Naive B...

For years, the traditional four-step travel demand forecasting model has helped the policy makers for making decisions regarding transportation programs and projects for metropolitan regions. This traditional model predicts the number of vehicles of each mode of transportation between the traffic analysis zones (TAZs) over a period of time. Althoug...

In this paper, Inverted L-Shape radiating patch with rectangular ground planer notch band monopole antenna is proposed. Antenna is fabricated on FR4 substrate with permittivity 4.4 and loss tangent 0.02 with dimension 12x8x1.6 mm3. Measured return loss is ≤ -10 dB for the entire impedance bandwidth 3.6 to 3.8 GHz and 4.8 to 16 GHz. Proposed antenna...

Forecasting is an integral part of any organization for their decision-making process so that they can predict their targets and modify their strategy in order to improve their sales or productivity in the coming future. This paper evaluates and compares various machine learning models, namely, ARIMA, Auto Regressive Neural Network(ARNN), XGBoost,...

The main objective of a text summarization system is to identify the most important information from the given text and present it to the end users. In this paper, Wikipedia articles are given as input to system and extractive text summarization is presented by identifying text features and scoring the sentences accordingly. The text is first pre-p...

To cope up with high speed demands of internet traffic, Optical Networks seems to be optimistic solution for Next Generation High Speed Network. An Optical Burst Switching (OBS) technology of Wavelength Division Multiplexing (WDM) has proved itself to satisfy current demands of the internet traffic. In OBS network, key concern is to reduce burst dr...

With an explosive growth of the Internet, optical network seems to be the candidate solution for future high-speed backbone networks. Optical burst switching (OBS) has been proposed as promising switching technology for the next generation wavelength division multiplexing (WDM) based network. The main issue in OBS based network is to reduce burst d...