A Review of Deep Learning Techniques for Leukemia Cancer Classification Based on Blood Smear Images by Rakhmonalieva Farangis Oybek Kizi, Tagne Poupi Theodore Armand, Hee-Cheol Kim

“…Using a systematic mapping study (SMS) and systematic literature review (SLR), thirty articles published between 2019 and 2023 were analyzed to explore the advancements in deep learning techniques for leukemia diagnosis using blood smear images. The analysis reveals that state-of-the-art models, such as Convolutional Neural Networks (CNNs), transfer learning, Vision Transformers (ViTs), ensemble methods, and hybrid models, achieved excellent classification accuracies. …”
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A New Comprehensive Well Logging Data Method for Evaluating Fracture Reservoir Productivity and Its Application by SHEN Qinyu, LI Shengqing, CUI Yunjiang, SU Yuanda, WANG Peichun, TANG Xiaoming

“…By using a multivariate statistical method, the factor analysis, this paper integrates the results of various logging methods, including acoustic, resistivity, borehole wall imaging, and other logging data to obtain controlling factors for the reservoir fluid transport property. …”
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Deep learning-based encryption scheme for medical images using DCGAN and virtual planet domain by Manish Kumar, Aneesh Sreevallabh Chivukula, Gunjan Barua

“…This paper presents a novel encryption technique that integrates the Deep Convolutional Generative Adversarial Networks (DCGAN) and Virtual Planet Domain (VPD) approach to enhance the protection of medical images. …”
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Event-based landslide inventory through very high-resolution optical images and field surveys by P. Confuorto, R. Franceschini, L. Scarpitta, N. Casagli, S. Morelli, F. Raspini, V. Tofani, S. Moretti

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New Release of User-Captured Images from the Oregon Health & Science University Melanoma MoleMapper Project by Tracy Petrie, Ravikant Samatham, Dan E. Webster, Sancy A. Leachman

“…These data are unlabelled but in a machine learning context can be used to pre-train networks using self-supervised learning techniques or to quantitatively analyze the image quality of consumer-collected skin images.…”
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A Robust Hybrid CNN+ViT Framework for Breast Cancer Classification Using Mammogram Images by Vasudha Rani Patheda, Gunda Laxmisai, B. V. Gokulnath, S. P. Siddique Ibrahim, S. Selva Kumar

“…This research addresses the variability and potential oversight in radiologists’ manual mammogram interpretations, aiming to enhance classification accuracy by combining Convolution Neural Networks (CNNs) and Vision Transformers (ViTs). CNN is a successful image classification that uses hierarchical feature extraction, ViTs capture the global context but require substantial data and computation. …”
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Mapping of Agate-like Soil Cover Structures Based on a Multitemporal Soil Line Using Neural Network Filtering of Remote Sensing Data by Dmitry I. Rukhovich, Polina V. Koroleva, Alexey D. Rukhovich, Mikhail A. Komissarov

“…ASCSs were identified over large areas and soil maps of ASCSs were constructed using multitemporal spectral characteristics of the BSS in the form of multitemporal soil line coefficients. Neural networks were used to identify BSS on big remote sensing data. …”
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Deep Learning for Cardiovascular Disease Detection by Shivan H. Hussein, Najdavan A. Kako

“…This work investigates the role and contribution of deep learning, especially Fully Convolutional Networks (FCNs) and Convolutional Neural Networks (CNNs), toward the improvement of accuracy and automation in cardiac MRI analysis. …”
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ICA-Based Resting-State Networks Obtained on Large Autism fMRI Dataset ABIDE by Sjir J. C. Schielen, Jesper Pilmeyer, Albert P. Aldenkamp, Danny Ruijters, Svitlana Zinger

“…One application of fMRI is investigating the brains of people with autism spectrum disorder (ASD). The Autism Brain Imaging Data Exchange (ABIDE) facilitates this research through its extensive data-sharing initiative. …”
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3D Convolutional Neural Networks for Brain Tumor Analysis in Multimodal MRI: A Systematic Review by Hamza S. Alsmadi, Hazlina Hamdan, Norwati Mustapha, Noridayu Manshor

“…Convolutional neural networks (CNNs) have emerged as a preferred approach for medical image analysis. …”
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Semantic Meta-Split Learning: A TinyML Scheme for Few-Shot Wireless Image Classification by Eslam Eldeeb, Mohammad Shehab, Hirley Alves, Mohamed-Slim Alouini

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A Staged Framework for Computer Vision Education: Integrating AI, Data Science, and Computational Thinking by In-Seong Jeon, Sukjae Joshua Kang, Seong-Joo Kang

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Fine-scale forest classification with multi-temporal sentinel-1/2 imagery using a temporal convolutional neural network by Rongfei Duan, Chunlin Huang, Peng Dou, Jinliang Hou, Ying Zhang, Juan Gu

“…A Temporal Convolutional Neural Network (TempCNN), which excels in handling temporal data and adapting to complex patterns, was constructed using TensorFlow with 133.8k parameters. …”
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CCMCS-Net: Integrating Color Correction and Multicolor-Space Stretching for Improving Underwater Image Quality by Jianjun Chen, Yujie Yang, Jingjing Song, Xibei Yang, Jinlong Shi

“…A color correction subnetwork and a multicolor-space stretching subnetwork are the two primary parts of the network. Initially, the static correction module (SCM) leverages green channel data to adjust the red and blue channels, correcting color distortion in degraded images. …”
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A hybrid multi-instance learning-based identification of gastric adenocarcinoma differentiation on whole-slide images by Mudan Zhang, Xinhuan Sun, Wuchao Li, Yin Cao, Chen Liu, Guilan Tu, Jian Wang, Rongpin Wang

“…Abstract Objective To investigate the potential of a hybrid multi-instance learning model (TGMIL) combining Transformer and graph attention networks for classifying gastric adenocarcinoma differentiation on whole-slide images (WSIs) without manual annotation. …”
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Identifying stochastic oscillations in single-cell live imaging time series using Gaussian processes. by Nick E Phillips, Cerys Manning, Nancy Papalopulu, Magnus Rattray

“…Pulsatile dynamics are thought to be widespread, and single-cell live imaging of gene expression has lead to a surge of dynamic, possibly oscillatory, data for different gene networks. …”
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Model and training method for aerial image object detector with optimization of both robustness and computational efficiency by Alona Moskalenko, Mykola Zaretskyi, Maksym Vynohradov, Vladyslav Babych

“…The subject of research is Neural network-based object detectors, which are widely used for video image analysis. …”
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Algorithm Comparison and Evaluation of GAN Models Based on Image Transferring from Desert to Green Field by Zhenyu Liu, Hongjun Li

“…In this paper, after comparing seven generative adversarial network (GAN) models in the way of theory analysis, we propose a method for generating green fields using desert images as input data, and a comprehensive comparison is presented on how GANs are currently applied to solve the desert-to-oasis problem. …”
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Clavulanic Acid-Mediated Increases in Anterior Cingulate Glutamate Levels are Associated With Decreased Cocaine Craving and Brain Network Functional Connectivity Changes by Joya Maser, MS, Mary F. Morrison, MD, Helene Philogene Khalid, PhD, Ronan Cunningham, Daohai Yu, PhD, M. Ingre Walters, MD, Xiaoning Lu, Nicolas R. Bolo, PhD

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Enhancing AES image encryption with a three-dimensional hyperchaotic system for increased security and efficiency. by Mingyi Huo, Yanpei Zheng, Jun Huang

“…Although the Advanced Encryption Standard (AES), a widely used symmetric encryption method, performs excellently in data communication and network security, its efficiency and security face significant challenges when directly applied to image encryption due to the inherent complexity of image data. …”
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