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Genetic Neural Architecture Search for automatic assessment of human sperm images
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In: ISSN: 0957-4174 ; Expert Systems with Applications ; https://hal.archives-ouvertes.fr/hal-03585035 ; Expert Systems with Applications, Elsevier, 2022 (2022)
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Abstract:
International audience ; Male infertility is a disease that affects approximately 7% of men. Sperm morphology analysis (SMA) is one of the main diagnosis methods for this problem. However, manual SMA is an inexact, subjective, nonreproducible, and hard to teach process. Therefore, in this paper, we introduce a novel automatic SMA technique that is based on the neural architecture search algorithm, named Genetic Neural Architecture Search (GeNAS). For this purpose, we used a collection of images termed MHSMA dataset, which contains 1, 540 sperm images that have been collected from 235 patients with infertility problems. In detail, GeNAS consists of a special genetic algorithm that acts as a meta-controller which explores the constrained search space of plain convolutional neural network architectures. Every individual of this genetic algorithm is a convolutional neural network trained to predict morphological deformities in different segments of human sperm (head, vacuole, and acrosome). The fitness of each individual is calculated by a novel proposed method, named GeNAS Weighting Factor (GeNAS-WF). This technique is specially designed to evaluate the fitness of neural networks which, during their learning process, validation accuracy highly fluctuates. To speed up the algorithm, a hashing method is practiced to save each trained neural architecture fitness, so we could reuse them during fitness evaluation. In terms of running time and computational power, our proposed architecture search method is far more efficient than most of the other existing neural architecture search algorithms. Moreover, whereas most of the existing neural architecture search algorithms are designed to work well with well-prepared benchmark datasets, the overall paradigm of GeNAS is specially designed to address the challenges of real-world datasets, particularly shortage of data and class imbalance. In our experiments, the best neural architecture found by GeNAS has reached an accuracy of 91.66%, 77.33%, and 77.66% in the vacuole, head, and acrosome abnormality detection, respectively. In comparison to other proposed algorithms for MHSMA dataset, GeNAS achieved state-of-the-art results.
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Keyword:
[INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]; [INFO.INFO-BI]Computer Science [cs]/Bioinformatics [q-bio.QM]; Deep Learning; Genetic Algorithm; Human Sperm Morphometry; Infertility; Neural Architecture Search
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URL: https://hal.archives-ouvertes.fr/hal-03585035
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Cross-lingual few-shot hate speech and offensive language detection using meta learning
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In: ISSN: 2169-3536 ; EISSN: 2169-3536 ; IEEE Access ; https://hal.archives-ouvertes.fr/hal-03559484 ; IEEE Access, IEEE, 2022, 10, pp.14880-14896. ⟨10.1109/ACCESS.2022.3147588⟩ (2022)
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Compiler-Driven Simulation of Reconfigurable Hardware Accelerators ...
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An Adversarial Attack Analysis on Malicious Advertisement URL Detection Framework ...
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Innovative Vineyards Environmental Monitoring System Using Deep Edge AI
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In: Artificial Intelligence for Digitising Industry Applications ; https://hal.univ-reims.fr/hal-03355270 ; Artificial Intelligence for Digitising Industry Applications, River Publishers, pp.261-278, 2021, 9788770226646 ; https://www.riverpublishers.com/research_details.php?book_id=967 (2021)
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Ontology as neuronal-space manifold: Towards symbolic and numerical artificial embedding
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In: KRHCAI 2021 Workshop on Knowledge Representation for Hybrid & Compositional AI @ KR2021 ; https://hal.inria.fr/hal-03360307 ; KRHCAI 2021 Workshop on Knowledge Representation for Hybrid & Compositional AI @ KR2021, Nov 2021, Hanoi, Vietnam (2021)
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Ontology as neuronal-space manifold: Towards symbolic and numerical artificial embedding
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In: KRHCAI 2021 Workshop on Knowledge Representation for Hybrid & Compositional AI @ KR2021 ; https://hal.inria.fr/hal-03360307 ; KRHCAI 2021 Workshop on Knowledge Representation for Hybrid & Compositional AI @ KR2021, Nov 2021, Hanoi, Vietnam (2021)
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Tra Intelligenza Artificiale e H-BIM per la descrizione semantica dei beni culturali: la Certosa di Pisa
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In: 42e Conférence internationale des enseignants des disciplines de la représentation ; https://hal.archives-ouvertes.fr/hal-03360124 ; 42e Conférence internationale des enseignants des disciplines de la représentation, Sep 2021, Reggio Calabria, Italy. ⟨10.3280/oa-693.33⟩ (2021)
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Ontology as neuronal-space manifold: Towards symbolic and numerical artificial embedding
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In: KRHCAI 2021 Workshop on Knowledge Representation for Hybrid & Compositional AI @ KR2021 ; https://hal.inria.fr/hal-03360307 ; KRHCAI 2021 Workshop on Knowledge Representation for Hybrid & Compositional AI @ KR2021, Nov 2021, Hanoi, Vietnam (2021)
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L'Art d'Anticiper les Changements IGP pour Acheminer Optimalement la Patate en Transit
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In: CORES 2021 – 6ème Rencontres Francophones sur la Conception de Protocoles, l’Évaluation de Performance et l’Expérimentation des Réseaux de Communication ; https://hal.archives-ouvertes.fr/hal-03221273 ; CORES 2021 – 6ème Rencontres Francophones sur la Conception de Protocoles, l’Évaluation de Performance et l’Expérimentation des Réseaux de Communication, Sep 2021, La Rochelle, France (2021)
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Reference Architectures for Smart Grids: Towards a Standard-based Comparative Framework
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In: International Conference on Engineering and Emerging Technologies (ICEET 2021) ; https://hal.archives-ouvertes.fr/hal-03439305 ; International Conference on Engineering and Emerging Technologies (ICEET 2021), Oct 2021, Istanbul, Turkey (2021)
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Architecture and augmented reality. A way of writing space : instrumented visual thinking ; Architecture et réalité augmentée. Une manière d’écrire l’espace : la pensée visuelle instrumentée
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In: https://tel.archives-ouvertes.fr/tel-03181642 ; Linguistique. Sorbonne Université, 2021. Français. ⟨NNT : 2021SORUL001⟩ (2021)
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Dataset of coronavirus content from Instagram with an exploratory analysis
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In: ISSN: 2169-3536 ; EISSN: 2169-3536 ; IEEE Access ; https://hal.archives-ouvertes.fr/hal-03559489 ; IEEE Access, IEEE, 2021, 9, pp.157192-157202. ⟨10.1109/ACCESS.2021.3126552⟩ (2021)
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Elastic Silicon Interconnects: Abstracting Communication in Accelerator Design ...
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HIR: An MLIR-based Intermediate Representation for Hardware Accelerator Description ...
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Machine Learning based Malicious Payload Identification in Software-Defined Networking ...
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A Bibliometric Analysis of Plant Disease Classification with Artificial Intelligence using Convolutional Neural Network
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In: Library Philosophy and Practice (e-journal) (2021)
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The pendulum type surfaces with congruential cross sections
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In: Structural Mechanics of Engineering Constructions and Buildings, Vol 17, Iss 2, Pp 165-174 (2021) (2021)
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Determining Tone of a Body of Text
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In: Senior Projects Spring 2020 (2020)
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