Object Detection and Recognition
Our team of experts can develop computer vision solutions for object detection and recognition using deep learning techniques such as convolutional neural networks (CNNs) and transfer learning.
We use popular frameworks like TensorFlow, PyTorch, and OpenCV to create accurate and efficient models that can detect and recognize objects in images.
Image Classification
Our team can also develop image classification solutions using ML algorithms like support vector machines (SVMs), k-nearest neighbors (k-NN), and decision trees.
These solutions can be used in a variety of applications such as medical imaging, satellite imaging, and product recognition.
Image Segmentation
We can provide image segmentation solutions that segment an image into multiple regions or objects of interest. This technique is widely used in medical imaging, computer vision, and autonomous driving.
We use techniques like watershed algorithm, graph cut algorithm, and U-Net architecture to create efficient and accurate segmentation models.
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