The HAM10000 dataset is a publicly available dataset used in the field of dermatology and machine learning for research related to the classification of skin lesions, particularly for the detection of skin cancer. “HAM” stands for “Human Against Machine,” signifying the goal of improving automated dermatological diagnoses through machine learning.

As biometric security becomes more common, we can’t ignore the risk of silicone masks in biometric attacks. Our AI data collection company is dedicated to giving you all the latest info on this changing threat.

This dataset is designed for those who are looking to undertake a binary classification project that’s both engaging and challenging.

The LISA Traffic Light Dataset is a well-known and widely used dataset in computer vision and autonomous driving research. It is designed to support the development and evaluation of algorithms for traffic light detection and recognition.

This data set contains 9 different types of flowers. Your task is to build a machine-learning or deep-learning model that can classify these images as flowers.

Found this dataset valuable? Support its growth and visibility in the community with an upvote. Your feedback helps enhance its reach and utility, making it a cornerstone for future explorations in aerial technology.

Semantic segmentation is a crucial computer vision technique used in the context of self-driving cars to understand and interpret the environment surrounding the vehicle. It involves the process of assigning semantic labels to each pixel in an image or a series of images, effectively segmenting the image into various meaningful objects or regions.

Adheres to ethical data usage standards, ensuring all content is appropriately licensed and suitable for a broad range of users.

Optimize waste collection strategies by locating cardboard disposal points accurately.

Dive into 17 Celebrity Worlds with 100 Glamorous Images Each