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Machine learning for surrogate process models of bioproduction pathways

Tyler Tarr Huntington, Nawa Raj Baral, Minliang Yang, Eric R. Sundstrom, Corinne Donahue Scown

Bioresource Technology 2022 cited by 36

Climate & Environment Microbial Metabolic Engineering and Bioproduction ai assisted importance 4/10 scale stated

Detailed process simulation models for biofuel and biochemical production are costly and computationally intensive, limiting sharing and reproduction.

Details Source Open-access PDF model: not stated in source

An evaluation of platforms for processing camera‐trap data using artificial intelligence

Juliana Vélez, William Joseph McShea, Hila Shamon, Paula J. Castiblanco‐Camacho, Michael A. Tabak, Carl Chalmers, Paul Fergus, John Fieberg

Methods in Ecology and Evolution 2022 cited by 133

Biology & Life Sciences Wildlife Ecology and Conservation ai assisted importance 4/10 scale stated

Processing the large volumes of images generated by camera traps is so time-consuming that it limits the efficiency of wildlife surveys.

Details Source Open-access PDF model: convolutional neural networks (CNNs)

Automatic Extraction of Indoor Spatial Information from Floor Plan Image: A Patch-Based Deep Learning Methodology Application on Large-Scale Complex Buildings

Hyunjung Kim, Seong-Yong Kim, Kiyun Yu

ISPRS International Journal of Geo-Information 2021 cited by 28

Engineering & Materials Automated Road and Building Extraction ai assisted importance 4/10 scale stated

Automatic extraction of indoor spatial information from floor plans was mostly demonstrated only on small, simple, low-resolution buildings.

Details Source Open-access PDF model: CNN (Convolutional Neural Network)

Machine Learning Techniques for Land Use/Land Cover Classification of Medium Resolution Optical Satellite Imagery Focusing on Temporary Inundated Areas

Boudewijn van Leeuwen, Zalán Tobak, Ferenc Kovács

Journal of Environmental Geography 2020 cited by 33

Climate & Environment Remote-Sensing Image Classification ai assisted importance 4/10 scale stated

Temporary inundations in flat agricultural areas of southern Hungary disrupt farming and cause large financial loss; mapping land use/land cover, especially inundated areas, from medium-resolution satellite imagery is needed.

Details Source Open-access PDF model: random forest, support vector machine, art...

Transforming Surgical Training With AI Techniques for Training, Assessment, and Evaluation: Scoping Review

David Escobar-Castillejos, Ari Yair Barrera-Animas, Julieta Noguez, Alejandra J. Magana, Bedřich Beneš

Journal of Medical Internet Research 2025 cited by 22

Medicine & Health Surgical Simulation and Training ai assisted importance 4/10 scale stated

Surgical training assessment and evaluation rely on traditional methods that may be improved by data-driven AI techniques.

Details Source Open-access PDF model: not stated in source

Reinforcement learning for mutation operator selection in automated program repair

Carol Hanna, Aymeric Blot, Justyna Petke

Automated Software Engineering 2025 cited by 9

Software & Coding Software Testing and Debugging Techniques ai assisted importance 4/10 scale stated

Heuristic-based automated program repair wastes resources because mutation operators are chosen uniformly at random, producing many uncompilable or functionality-breaking program variants.

Details Source Open-access PDF model: not stated in source

Transformer-based land use and land cover classification with explainability using satellite imagery

Mehak Khan, Abdul Hanan, Meruyert Kenzhebay, Michele Gazzea, Reza Arghandeh

Scientific Reports 2024 cited by 66

Climate & Environment Remote-Sensing Image Classification ai assisted importance 4/10 scale stated

Transformer models for land use and land cover (LULC) analysis from satellite imagery are too computationally expensive for practical use.

Details Source Open-access PDF model: Transformer-based models with transfer lea...

Cross-modality transformations in biological microscopy enabled by deep learning

Dana Hassan, Jesús Domínguez, Benjamin Midtvedt, Henrik Klein Moberg, Jesús D. Pineda, Christoph Langhammer, Giovanni Volpe, Antoni Homs-Corbera et al.

Advanced Photonics 2024 cited by 23

Biology & Life Sciences Advanced Image Processing Techniques ai assisted importance 4/10 scale stated

Deep-learning methods can virtually transform microscopy images across optical modalities, but biologists lack a unified overview, limiting adoption in daily research and clinical trials.

Details Source Open-access PDF model: not stated in source

Generative machine learning produces kinetic models that accurately characterize intracellular metabolic states

Subham Choudhury, Bharath Narayanan, Michaël Moret, Vassily Hatzimanikatis, Ljubiša Mišković

Nature Catalysis 2024 cited by 64

Biology & Life Sciences Microbial Metabolic Engineering and Bioproduction ai assisted importance 4/10 scale stated

Determining kinetic parameters for large-scale metabolic models is difficult, hindering integration of omics data and broader adoption of these models.

Details Source Open-access PDF model: RENAISSANCE

Classification of Low Earth Orbit (LEO) Resident Space Objects’ (RSO) Light Curves Using a Support Vector Machine (SVM) and Long Short-Term Memory (LSTM)

Randa Qashoa, Regina Lee

Sensors 2023 cited by 27

Physics & Astronomy Space Satellite Systems and Control ai assisted importance 4/10 scale stated

Classifying short light curves of low Earth orbit resident space objects to infer object type, attitude and shape.

Details Source Open-access PDF model: SVM and LSTM with wavelet scattering trans...

Supplementing recurrent neural networks with annealing to solve combinatorial optimization problems

Shoummo Ahsan Khandoker, Jawaril Munshad Abedin, Mohamed Hibat-Allah

Machine Learning Science and Technology 2023 cited by 14

Mathematics Metaheuristic Optimization Algorithms Research ai assisted importance 4/10 scale stated

Simulated annealing suffers slow convergence and gets stuck in local search spaces when solving combinatorial optimization problems like Max-Cut, nurse scheduling, and TSP.

Details Source Open-access PDF model: VCA (variational classical annealing) with...

Efficient Deep Semantic Segmentation for Land Cover Classification Using Sentinel Imagery

Anastasios Tzepkenlis, Konstantinos Marthoglou, Nikos Grammalidis

Remote Sensing 2023 cited by 55

Climate & Environment Remote-Sensing Image Classification ai assisted importance 4/10 scale stated

Land cover classification is hindered by time-consuming annotation, imagery download, and pre-processing tasks that discourage policy makers from creating and using new land cover maps.

Details Source Open-access PDF model: Modified U-TAE semantic segmentation model

Automated visitor and wildlife monitoring with camera traps and machine learning

Veronika Mitterwallner, Anne Peters, Hendrik Edelhoff, Gregor Mathes, Hien Nguyen, Wibke Peters, Marco Heurich, Manuel J. Steinbauer

Remote Sensing in Ecology and Conservation 2023 cited by 42

Climate & Environment Wildlife Ecology and Conservation ai assisted importance 4/10 scale stated

Manually classifying hundreds of thousands of camera trap images to study human–wildlife interactions is slow and labor-intensive.

Details Source Open-access PDF model: MegaDetector

Machine learning explainability in nasopharyngeal cancer survival using LIME and SHAP

Rasheed Omobolaji Alabi, Mohammed Salem Elmusrati, Ilmo V.V. Leivo, Alhadi Almangush, Antti A. Mäkitie

Scientific Reports 2023 cited by 160

Medicine & Health Explainable Artificial Intelligence (XAI) ai assisted importance 4/10 scale stated

Nasopharyngeal cancer patients attain different outcomes and need prognostic stratification into low and high survival groups.

Details Source Open-access PDF model: Stacked ensemble of five ML algorithms wit...

Deep Learning for Skin Melanocytic Tumors in Whole-Slide Images: A Systematic Review

Andrés Mosquera‐Zamudio, Laëtitia Launet, Zahra Tabatabaei, Rafael Santiago Parra-Medina, Adrián Colomer, Javier Oliver Moll, Carlos Couceiro Monteagudo, Emiel A. M. Janssen et al.

Cancers 2022 cited by 33

Medicine & Health AI in cancer detection ai assisted importance 4/10 scale stated

Histological interpretation of melanocytic tumors is challenging and subject to interobserver variability between dermatopathologists.

Details Source Open-access PDF model: Deep learning; specific architectures not...

Additive manufacturing: A machine learning model of process-structure-property linkages for machining behavior of Ti-6Al-4V

Xi Gong, Dongrui Zeng, Willem Groeneveld-Meijer, Guha P. Manogharan

Materials Science in Additive Manufacturing 2022 cited by 47

Engineering & Materials Additive Manufacturing Materials and Processes ai assisted importance 4/10 scale stated

A knowledge gap exists in how additive manufacturing processes and heat treatments link to microstructure and machining behavior of Ti-6Al-4V parts.

Details Source Open-access PDF model: not stated in source