InfoQ

DoorDash Builds DashCLIP to Align Images, Text, and Queries for Semantic Search Using 32M Labels

DoorDash has launched a multimodal machine learning system that aligns product images, text, and user queries in a shared ...
Hosted on MSN

Image classification with CNNs in Keras | Easy guide

In this video, we will implement Image Classification using CNN Keras. We will build a Cat or Dog Classification model using CNN Keras. Keras is a free and open-source high-level API used for neural ...
GitHub

[FEAT]: Part 2.2: Build baseline MNIST CNN

Build, train, and evaluate a Convolutional Neural Network (CNN) for classifying the MNIST handwritten digits dataset using either TensorFlow or PyTorch. The primary goal is to create a model that ...
Scientific Research Publishing

Hem-CNN: An Efficient Intracranial Hemorrhage Detection Model Using Explainable Deep Learning in Head CT Scan Images ()

1 Department of Computer Science, American International University-Bangladesh (AIUB), Dhaka, Bangladesh. 2 Department of Electrical and Electronics Engineering, American International ...
IEEE

Cross-Domain Hyperspectral Image Classification via Mamba–CNN and Knowledge Distillation

Abstract: Domain adaptation (DA)-based cross-domain hyperspectral image (HSI) classification methods have garnered significant attention. The majority of DA techniques utilize models based on ...
GitHub

MinOS-WJ/CNN-MNIST

• Architecture: 4-layer CNN (convolutional layers with 32, 64, 128, and 256 filters) → Max pooling → Dropout → Fully connected layers. • Training: Dataset: MNIST (28×28 grayscale digits).
IEEE

Kannada-Mnist Classification Using Skip CNN

Abstract: In this paper, we tried out a new pipeline on the new handwritten digits dataset termed Kannada-MNIST for the Kannada script as well as a real-world handwritten dataset termed Dig-MNIST. The ...