8 Result(s)
within
Computational Intelligence
Jyothisha J. Nair
Conference Paper
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Chapter and Conference Paper
Nuclei Segmentation Using UNet with EfficientNetV2 as Encoder
Nucleus segmentation of H &E-stained (hematoxylin and eosin) histopathology images is a crucial step in develo** a computer-aided diagnostic (CAD) system for cancer prediction and diagnosis. Nucleus segmenta...
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Chapter and Conference Paper
Deep Learning Approach for Brown Spot Detection and Nitrogen Deficiency Estimation in Rice Crops
More than half of the people in the world rely on rice as their primary energy source. Two main challenges in rice cultivation are plant diseases and nutrient deficiency. Brown spots on leaves caused by the fu...
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Chapter and Conference Paper
Ensemble Deep Learning Model for Breast Histopathology Image Classification
Breast cancer is a life-threatening disease that affects individuals all over the world. As a consequence, effective and precise breast cancer screening is crucial. Early detection of breast cancer allows pati...
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Chapter and Conference Paper
Exploring SVM for Federated Machine Learning Applications
The traditional machine learning algorithms focus on centralised data repository where the aggregate data used for training is stored in a common location and processed. This approach is not suitable when data...
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Chapter and Conference Paper
Copy-Move Forgery Detection Using BEBLID Features and DCT
Images can act as a source of information, with the advancement in editing tools anyone can tamper an image effortlessly. Authenticity of the data we get is something very important and hence becomes an essent...
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Chapter and Conference Paper
Compact-VG: A Small-scale Dataset for Scene Graph Generation
High-level image understanding includes phases like object detection, predicate classification, and attribute classification. The outputs from each phase are merged to build a scene graph, which arranges the...
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Chapter and Conference Paper
Computing Articulation Points Using Maximal Clique-Based Vertex Classification
The bridge vertices of an unweighted undirected graph are those vertices whose removal increases the number of connected components of the graph, i.e., the vertices whose removal disconnects the graph. However...
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Chapter and Conference Paper
Speckle Noise Reduction Using Fourth Order Complex Diffusion Based Homomorphic Filter
Filtering out speckle noise is essential in many imaging applications. Speckle noise creates a grainy appearance that leads to the masking of diagnostically significant image features and consequent reduction ...
