Enhancing Deepfake Detection Through Quantum Transfer Learning and Class-Attention Vision Transformer Architecture by Bekir Eray Katı, Ecir Uğur Küçüksille, Güncel Sarıman

“…Deepfake detection has become a critical research topic in both academic and practical domains, as it involves identifying forged elements in artificially generated videos using various deep learning and artificial intelligence techniques. …”
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Interpretable DWT-1DCNN-LSTM Network for Power Quality Disturbance Classification by Shuangquan Yang, Tao Shan, Xiaomei Yang

“…Accurate identification of these disturbances is crucial for effective grid management and protection. Although deep learning methods have high accuracy, their lack of interpretability can limit their acceptance in engineering applications. …”
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IoT-Based Pest Detection in Agriculture Using Raspberry Pi and YOLOv10m for Precision Farming by Zarboubi Mohamed, Bellout Abdelaaziz, Chabaa Samira, Dliou Azzedine, Zeroual Abdelouhab

“…Ultimately, this research makes a substantial contribution to precision agriculture by harnessing the synergies of deep learning and IoT technologies, delivering a dependable and cost-effective solution for managing pest populations in agriculture.…”
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An Adversarial Attack via Penalty Method by Jiyuan Sun, Haibo Yu, Jianjun Zhao

“…Deep learning systems have achieved significant success across various machine learning tasks. …”
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Dynamic Prediction of Physical Exertion: Leveraging AI Models and Wearable Sensor Data During Cycling Exercise by Aref Smiley, Joseph Finkelstein

“…<b>Methods</b>: Both traditional machine learning and deep learning methods for classification and regression were assessed. …”
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SaliencyMix&#x002B;: Noise-Minimized Image Mixing Method With Saliency Map in Data Augmentation by Hajeong Lee, Zhixiong Jin, Jiyoung Woo, Byeongjoon Noh

“…Data augmentation is vital in deep learning for enhancing model robustness by artificially expanding training datasets. …”
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Fish oocyte morphology detection using neural networks: a comparison of YOLO architectures by Yanna Leidy Ketley Fernandes Cruz, Ewaldo Eder Carvalho Santana, Isa Rosete Araujo Nascimento, Antonio Fhillipi Maciel Silva, Raimunda Nonata Fortes Carvalho Neta, José Ribamar de Souza Torres-Junior

“…With the development of deep learning techniques, automatic object detection has become an important mechanism for this task. …”
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Human activity recognition: an approach 2D CNN-LSTM to sequential image representation and processing of inertial sensor data by Wallace Camacho Carlos, Alessandro Copetti, Luciano Bertini, Leonard Barreto Moreira, Otávio de Souza Martins Gomes

“…The field of human activity recognition, abbreviated as HAR, benefits significantly from deep learning by addressing the complexity of human behavior and the vast volume of data produced by sensors. …”
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Developing an Intelligent System for Efficient Botnet Detection in IoT Environment by Ramesh Singh Rawat, Manoj Diwakar, Umang Garg, Prakash Srivastava

“…Thus, effective machine learning is required to solve these security issues. Additionally, deep learning with the necessary elements is advised to defend the network from these threats. …”
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An Enhanced Deep Neural Network for Predicting Workplace Absenteeism by Syed Atif Ali Shah, Irfan Uddin, Furqan Aziz, Shafiq Ahmad, Mahmoud Ahmad Al-Khasawneh, Mohamed Sharaf

“…In this paper, we propose Neural Networks and Deep Learning algorithms that can predict the behavior of employees towards punctuality at workplace. …”
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A Novel Oil Spill Dataset Augmentation Framework Using Object Extraction and Image Blending Techniques by Farkhod Akhmedov, Halimjon Khujamatov, Mirjamol Abdullaev, Heung-Seok Jeon

“…Several studies have mentioned that the quality and size of a dataset is crucial for training robust vision-based deep learning models. The proposed methodology combines advanced object extraction techniques with traditional data augmentation strategies to generate high quality and realistic oil spill images under various oceanic conditions. …”
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Constructing Attention-LSTM-VAE Power Load Model Based on Multiple Features by Chaoyue Ma, Ying Wang, Feng Li, Huiyan Zhang, Yong Zhang, Haiyan Zhang

“…Therefore, the performance of the Attention-LSTM-VAE model is better than the general deep learning load models, which has important reference for the research of power load models. …”
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Comparative analysis of transfer learning performance on generalised EEG data for use in a depression diagnosis task by Shusharina, Natalia Nikolaevna

“…The purpose of this work was to analyse the performance of different deep learning methods in the task of depression diagnosis based on bioelectrical brain activity data. …”
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Mapping fruit tree dynamics using phenological metrics from optimal Sentinel-2 data and Deep Neural Network by Yingisani Chabalala, Elhadi Adam, Mahlatse Kganyago

“…This creates new possibilities for deep learning to revolutionize and facilitate innovation within smart horticulture.…”
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LEAF-YOLO: Lightweight Edge-Real-Time Small Object Detection on Aerial Imagery by Van Quang Nghiem, Huy Hoang Nguyen, Minh Son Hoang

“…Advances in Unmanned Aerial Vehicles (UAVs) and deep learning have spotlighted the challenges of detecting small objects in UAV imagery, where limited computational resources complicate deployment on edge devices. …”
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Enhancing prostate cancer segmentation in bpMRI: Integrating zonal awareness into attention-guided U-Net by Chao Wei, Zheng Liu, Yibo Zhang, Lianhui Fan

“…This research not only enhances the field of medical imaging for oncology but also underscores the potential of deep learning models to progress PCa diagnosis and personalized patient care.…”
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Enhancing thyroid disease prediction and comorbidity management through advanced machine learning frameworks by P. Sanju, N. Syed Siraj Ahmed, P. Ramachandran, P. Mohamed Sajid, R. Jayanthi

“…Utilizing the UCI Thyroid Dataset, the framework combines the strengths of deep learning-based feature extraction and traditional machine learning classifiers. …”
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Homogenized Point Mutual Information and Deep Quantum Reinforced Wind Power Prediction by W. G. Jency, J. E. Judith

“…There are numerous common and deep learning methods that have evolved to attain wind power prediction. …”
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Precise Crop Pest Detection Based on Co-Ordinate-Attention-Based Feature Pyramid Module by Chenrui Kang, Lin Jiao, Kang Liu, Zhigui Liu, Rujing Wang

“…Fast and precise pest detection and counting are crucial measures in the management and mitigation of pest infestations. In this area, deep learning technologies have come to represent the method with the most potential. …”
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cigFacies: a massive-scale benchmark dataset of seismic facies and its application by H. Gao, X. Wu, X. Sun, M. Hou, M. Hou, H. Gao, G. Wang, H. Sheng

“…However, unlike the CV domain, the field of seismic exploration lacks a comprehensive benchmark dataset for seismic facies, severely limiting the development, application, and evaluation of deep-learning approaches in seismic facies classification. …”
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