Enhancing human-dog interaction through deep learning and explainable AI

An explainable AI framework integrating machine and deep learning models for multi-species DNA functional group classification

Pratik Chakraborty, P. B. Shanthi

Abstract DNA functional group classification across species plays a crucial role in understanding genetic diversity, evolutionary relationships and biological function. The increasing availability of genomic data has led to the use of machine learning and deep learning methods fo…Read more

A hybrid explainable deep learning framework for blood cancer classification using CNN-based feature embeddings and random forest decision models

Zulfikar Ali Ansari, Hemlata Pant, Nayancy, M. N. V. Kiranbabu, Sanjeet Kumar

The precision and early detection of subtypes of acute lymphoblastic leukaemia (ALL) in peripheral blood smear images are crucial for efficient clinical practice. Traditional deep learning methods tend to be challenging in terms of model interpretation and are often reliant on la…Read more

Hybrid fusion of E-nose and computer vision using optimized deep learning and machine learning for robust plant leaf recognition

Pouya Bohlol, Mohammad Hasan Sabet Dizavandi, Syed Saeid Mohtasebi, Mahmoud Omid

Abstract The fusion multi-sensory system with optimized deep learning and machine learning algorithms appeared to synergize difficult paradigms in precision agriculture and boost recognition of various plant species. In this study, an electronic nose (E-nose) system with eight MO…Read more

Exploring feature limitations in antimicrobial resistance prediction: machine learning and deep learning in A. baumannii

Zahra Seraj, Zahra Ghorbanali, Fatemeh Zare-Mirakabad, Bahareh Attaran, Sajjad Gharaghani

HybridSwingNet for explainable swing trading using multi-encoder deep learning and confidence-calibrated signal execution

G. B. Sambare, Swati Shinde, Onkar Jadhav, Harsh Itkar, Lalit Deore, Sarthak Joshi, et al.

Hybrid deep learning framework for detection of lateral movement in advanced persistent threats

Balaganesh Bojarajulu, M. Sethumadhavan, Vasily Sachnev, P. P. Amritha

Advanced persistent threats often use stolen or legitimate credentials to move stealthily across networks, making them difficult to detect with traditional security systems. This study introduces a novel framework called dual classifier-based lateral movement detection (DC-LMD-AP…Read more