MIT-World Peace University (MIT-WPU) is a top educational institute located in Pune, India. It is recognized within&nbsp;UGC under Government of Maharashtra Act No. XXXV 2017.&nbsp;

It is part of the MIT group of institutions (established in 1983) which covers 10+ campuses across India and has more than 50,000+ students enrolled across various disciplines at a given point of time. The institute houses 15 schools ranging from Engineering &amp; Technology, Design, Pharmacy, Commerce, Governance among others. It offers undergraduate, postgraduate and PhD programs among different disciplines.&nbsp;

&nbsp;

MIT World Peace University

School of Computer Engineering & Technology

The globe's population is increasing day by day, which causes the severe problem of organic food for everyone. Farmers are becoming progressively conscious of the need to control numerous essential factors such as crop health, water or fertilizer use, and harmful diseases in the field. However, it is challenging to monitor agricultural activities. Therefore, precision agriculture is an important decision support system for food production and decision-making. Several methods and approaches have been used to support precision agricultural practices. The present study performs a systematic literature review on hyperspectral imaging technology and the most advanced deep learning and machine learning algorithm used in agriculture applications to extract and synthesize the significant datasets and algorithms. We reviewed legal studies carefully, highlighted hyperspectral datasets, focused on the most methods used for hyperspectral applications in agricultural sectors, and gained insight into the critical problems and challenges in the hyperspectral data processing. According to our study, it has been found that the Hyperion hyperspectral, Landsat-8, and Sentinel 2 multispectral datasets were mainly used for agricultural applications. The most applied machine learning method was support vector machine and random forest. In addition, the deep learning-based Convolutional Neural Networks (CNN) model is mainly used for crop classification due to its high performance with hyperspectral datasets. The present review will be helpful to the new researchers working in the field of hyperspectral remote sensing for agricultural applications with a machine and deep learning methods. © 2022 Elsevier B.V.

World University root node

Engineering and Technology

Ecological Informatics

A systematic review on hyperspectral imaging technology with a machine and deep learning methodology for agricultural applications

Tehni{\v{c}}ki glasnik

Salient Features Selection Techniques for Instruction Detection in Mobile Ad Hoc Networks

Human affect is an important consideration in several cognitive and AI-driven applications. Efficient and timely determination of affect is crucial in detecting various physiological and psychological illnesses affecting humans globally. Cognitive science advocates the use of different modalities such as voice, text, images, and gestures in initiating/promoting human cognition. Thus, multimodality is an inherent nature of cognition. In this work, we have performed experimentation on real-time voice samples collected from four participants and attempted to determine patterns of affect. With suitable use of spectrogram, chroma features, beats, etc., we present various visualizations that depict the inter-individual acoustic differences. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Lecture Notes in Electrical Engineering

Use of Speech Analysis in Determining Human Affect: A Proof of Concept

2022 IEEE International Conference on Blockchain and Distributed Systems Security, ICBDS 2022

Virtual Mouse Using Hand Gesture Recognition - A Systematic Literature Review

Studies in Computational Intelligence

Deep Reinforcement-Based Conversational AI Agent in Healthcare System

Proceedings - International Conference on Applied Artificial Intelligence and Computing, ICAAIC 2022

A Comparison of Oversampling and Undersampling Methods for Predicting Air Quality in Metropolitan Region

Web Intelligence

Big data clustering using fractional sail fish-sparse fuzzy C-means and particle whale optimization based MapReduce framework

Human activity detection has become a prime research area in computer vision problem. There are many applications where human activity detection can be incorporated such as analyzing the video data which will help to monitor data generated by closed-circuit television (CCTV) cameras. In this paper, a system is proposed which uses convolutional neural network along with incremental learning to detect different type human activities in videos. The proposed system is evaluated on benchmark dataset, KTH dataset. © 2022 IEEE.

2022 2nd International Conference on Intelligent Technologies, CONIT 2022

Video-Based Human Activity Detection

2022 6th International Conference on Computing, Communication, Control and Automation, ICCUBEA 2022

Blockchain based Trusted Secure Philanthropy Platform: Crypto-GoCharity

Lecture Notes in Networks and Systems

An Optimistic Approach for Managing the Handover Latency by Using Dynamic Data in Software Defined Networks (SDN)