ARCHIVE

Medicinal Leaf Identification Using Deep Learning

Authors : Jay Khapare , Dimple Kumar , Komal Bhende, Aarya Babhulkar, Prof.Roshan Kotkondawar DOI : 10.46335/IJIES.2024.9.8.14 Abstract: Identification of medicinal plants or leaves plays an important role in many fields such as medicine, agriculture and conservation. The routine process of plant identification is often time consuming and requires botanical knowledge. In recent years, deep learning […]

Advancing Breast Cancer Detection Through Thermal Imaging and Machine Learning: A Comprehensive Review of Techniques and Applications

Authors : Vishakha Dubey, Dr. Shanti Rathore, Dr. Rahul Gedam DOI : 10.46335/IJIES.2025.10.7.17 Abstract – Breast thermography proves to be an evolving diagnostic support method that uses infrared imaging for vascular and metabolic change detection in breast cancer evaluations. This paper conducts an extensive analysis of thermographic imaging progress along with AI-based and ML-based diagnostic […]

Effective Ensemble Deep Learning Approach to Coronary Heart Disease Prediction

Authors : Deepak Yashwantrao Bhadane, Prof. Dr. Indrabhan S. Borse, Prof. Dr. Balveer Singh DOI :10.46335/IJIES.2025.10.6.8 Abstract – Cardiovascular disease is an important global challenge, and timely identification along with effective treatment relies on the accurate diagnosis of the condition. This work seeks to increase the precision of cardiovascular disease prediction by utilizing ensemble deep […]

Deep Reinforcement Learning for Face Anti-Spoofing

Authors : Saidur Rahman, Sahil Kumar, Dr M.Sujitha, P.Sudarsan DOI : 10.46335/IJIES.2025.10.8.18 Abstract – Spoofing detection has become a crucial and essential application for verifying security breaches. The Face Anti-Spoofing issue has made significant progress in recent years. This research addresses the problem of detecting spoofing images from unknown sources using deep learning algorithms. Specifically, […]

Literature Survey on Intelligent Rainfall Prediction Systems Using Advanced Machine Learning Algorithms

Authors : Dr.M.V.Bramhe, Rushab Katekhaye, Manthan Raut, Sharwari Sonulkar,Yash Dhande, Mrs. Sangita Rajankar DOI : 10.46335/IJIES.2025.10.5.3 Abstract – Rainfall prediction is crucial to efficient water resource management, agriculture, and catastrophe avoidance. Statistical models have gained popularity, yet machine learning approaches are progressively boosting prediction accuracy. SARIMA stands out for the ability to understand seasonal and […]