A hybrid parallel convolutional spiking neural network for enhanced skin cancer detection by K. Anup Kumar, C. Vanmathi

“…When the condition of illness worsens, the chance of survival is reduced, and thus detection of skin cancer is extremely difficult. Hence, this paper introduces a new model, known as Parallel Convolutional Spiking Neural Network (PCSN-Net) for detecting skin cancer. …”
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Harnessing infrared thermography and multi-convolutional neural networks for early breast cancer detection by Omneya Attallah

“…The Thermo-CAD system is assessed utilising two datasets: the DMR-IR (Database for Mastology Research Infrared Images), for distinguishing between normal and abnormal breast tissues, and a novel thermography dataset to distinguish abnormal instances as benign or malignant. Thermo-CAD has proven to be an outstanding CAD system for thermographic breast cancer detection, attaining 100% accuracy on the DMR-IR dataset (normal versus abnormal breast cancer) using CSVM and MGSVM classifiers, and lower accuracy using LSVM and QSVM classifiers. …”
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Electricity Theft Detection Using Rule-Based Machine Leaning (rML) Approach by Sheyda Bahrami, Erol Yumuk, Alper Kerem, Beytullah Topçu, Ahmetcan Kaya

“…Even though consumption-based models have been applied extensively to the detection of power theft, it can be difficult to reliably identify theft instances based only on patterns of usage. …”
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Soft detection model of corrosion leakage risk based on KNN and random forest algorithms by Yang YANG, Chengzhi LI, Xuan DU, Xiao YU, Shaohua DONG

“…Corrosion leakage risk assessment necessitates the comprehensive integration of risk assessment factors with various detection operations. Current detection tasks face challenges due to data complexities and significant data deficiencies. …”
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A Cost-Sensitive Small Vessel Detection Method for Maritime Remote Sensing Imagery by Zhuhua Hu, Wei Wu, Ziqi Yang, Yaochi Zhao, Lewei Xu, Lingkai Kong, Yunpei Chen, Lihang Chen, Gaosheng Liu

“…Specifically, at the dataset level, we select vessel targets appearing in the original dataset as templates and randomly copy–paste several instances onto arbitrary positions. This enriches the diversity of target samples per image and mitigates the impact of data imbalance on the detection task. …”
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DVAEGMM: Dual Variational Autoencoder With Gaussian Mixture Model for Anomaly Detection on Attributed Networks by Wasim Khan, Mohammad Haroon, Ahmad Neyaz Khan, Mohammad Kamrul Hasan, Asif Khan, Umi Asma Mokhtar, Shayla Islam

“…However, they suffer from the problem of ignoring the latent codes’ embedding distribution, which results in poor representation in many instances. In this paper, we propose a new framework called DVAEGMM to detect anomalies on attributed networks. …”
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Bringing Intelligence to SAR Missions: A Comprehensive Dataset and Evaluation of YOLO for Human Detection in TIR Images by Mostafa Rizk, Israa Bayad

“…The achieved inference rates along with the achieved detection performances meet with the requirement of fast detection of humans in SAR missions.…”
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A Novel Model-Based Reinforcement Learning for Online Anomaly Detection in Smart Power Grid by Ling Wang, Yuanzhe Zhu, Wanlin Du, Bo Fu, Chuanxu Wang, Xin Wang

“…There have been many outlier detection methods presented in the studies, varying from those requiring instance-by-instance decisions t the online diagnosing methods that require the use of accurate models of an attack. …”
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Extreme R-CNN: Few-Shot Object Detection via Sample Synthesis and Knowledge Distillation by Shenyong Zhang, Wenmin Wang, Zhibing Wang, Honglei Li, Ruochen Li, Shixiong Zhang

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Detection of West Nile virus via retrospective mosquito arbovirus surveillance, United Kingdom, 2025 by Arran J Folly

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RecyBat24: a dataset for detecting lithium-ion batteries in electronic waste disposal by Ximena Carolina Acaro Chacón, Fabrizio Lo Scudo, Gregorio Cappuccino, Carmine Dodaro

“…Additionally, we demonstrate how the RecyBat24’s detection-oriented annotations can be used to create a second version of RecyBat24for instance-segmentation tasks. …”
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Small sample smart contract vulnerability detection method based on multi-layer feature fusion by Jinlin Fan, Yaqiong He, Huaiguang Wu

“…To the best of our knowledge, this is the first instance of multi-layer feature sequence fusion in the field of smart contract vulnerability detection. …”
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Automatic image segmentation using Region-Based convolutional networks for Melanoma skin cancer detection by Karen Dayana Tovar-Parra, Luis Alexander Calvo-Valverde, Ernesto Montero-Zeledón, Mac Arturo Murillo-Fernández, Jose Esteban Perez-Hidalgo, Dionisio Alberto Gutiérrez-Fallas

“…The neural network model is focused on providing instance segmentation rather than only a boxbounding object detection. …”
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LADOS: Aerial Imagery Dataset for Oil Spill Detection, Classification, and Localization Using Semantic Segmentation by Konstantinos Gkountakos, Maria Melitou, Konstantinos Ioannidis, Konstantinos Demestichas, Stefanos Vrochidis, Ioannis Kompatsiaris

“…Oil spills on the water surface pose a significant environmental hazard, underscoring the critical need for developing Artificial Intelligence (AI) detection methods. Utilizing Unmanned Aerial Vehicles (UAVs) can significantly improve the efficiency of oil spill detection at early stages, reducing environmental damage; however, there is a lack of training datasets in the domain. …”
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MC-EVM: A Movement-Compensated EVM Algorithm with Face Detection for Remote Pulse Monitoring by Abdallah Benhamida, Miklos Kozlovszky

“…Automated tasks, mainly in the biomedical field, help to develop new technics to provide faster solutions for monitoring patients’ health status. For instance, they help to measure different types of human bio-signal, perform fast data analysis, and enable overall patient status monitoring. …”
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Basketball robot object detection and distance measurement based on ROS and IBN-YOLOv5s algorithms. by Jirong Zeng, Jingjing Fu

“…In the software layer of the object detection system, an algorithm that combines YOLOv5s and laser detection was used, and an appropriate instance batch normalization network module was introduced in the YOLOv5s algorithm to improve the model's generalization ability. …”
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Development and Validation of the ELISA Method for Neutralizing Anti-trastuzumab Antibodies Detection in Human Blood Serum by M. A. Kolganova, O. S. Sagimbaeva, Ju. S. Borisova, E. E. Beketov, I. E. Shokhin

“…The neutralizing anti-trastuzumab antibody determination was carried out by the competitive ELISA method, using spectrophotometric detection in the visible range of the spectrum.Results and discussion. …”
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Semi-Supervised Nuclei Detection in Histopathology Images via Location-Aware Adversarial Image Reconstruction by Chenchen Tian, Lei Su, Zhi Wang, Ao Li, Minghui Wang

“…Nuclei detection is a fundamental task for numerous downstream analysis of histopathology images. …”
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Interpretable multitask deep learning model for detecting and analyzing severity of rice bacterial leaf blight by Sudhesh K. M, Aarthi R., Sainamole Kurian. P, Sikha O.K

“…Abstract Rice Bacterial Leaf Blight (BLB), caused by Xanthomonas oryzae pv. oryzae (Xoo), is a major threat to rice production due to its rapid spread and widespread impact. Early detection and stage-specific classification of BLB are essential for timely intervention, particularly in complex environments with cluttered backgrounds and overlapping symptoms. …”
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Detection and position evaluation of chest percutaneous drainage catheter on chest radiographs using deep learning. by Duk Ju Kim, In Chul Nam, Doo Ri Kim, Jeong Jae Kim, Im-Kyung Hwang, Jeong Sub Lee, Sung Eun Park, Hyeonwoo Kim

“…Its performance in detecting the catheter and assessing its position on chest radiographs was evaluated by per radiographs and per instances. …”
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