In the realm of machine learning, image classification involves training a model to categorize images into predefined classes or labels. This process entails feeding a model with a dataset of labeled images, allowing it to learn to recognize distinctive features and patterns associated with each class. Conventional Neural Network models such as ResNet, VGG, Inception, MobileNet, and EfficientNet are commonly employed for this task due to their ability to automatically learn hierarchical representations of images. During training, the model adjusts its parameters to minimize the difference between predicted and actual labels, thus improving its accuracy in classifying unseen images. Once trained, the model can be deployed to classify new images, making it essential in various applications that need categorization of data.

At our company, we pride ourselves on being the premier choice for image labeling services to facilitate the training of image classification models. Our dedication to excellence and commitment to quality ensure that every labeled image we provide contributes significantly to the success of your machine learning projects. With a team of experienced annotators and quality assurance specialists, we guarantee accurate and consistent annotations that meet the highest industry standards. Moreover, our streamlined processes and efficient workflows allow us to offer competitive pricing without compromising on the quality of our services. Whether you’re a small startup or a large enterprise, we tailor our labeling solutions to suit your specific needs and budget. By choosing us, you’re not just getting a labeling service; you’re partnering with a trusted ally in your quest for superior machine learning outcomes.

Transparent Pricing Structure

We  follow a clear pricing structure for our image classification annotation services. Here’s a breakdown of the key pricing structure:

To initiate work, you prepay a portion of the total cost based on the batch size, tiered upfront payments are as follow:

After the annotations are complete, you pay the remaining balance based on the per-annotation cost.

Understanding Project Complexity

We understand that for some projects, especially those involving complex or subjective image classification tasks, accurately estimating the number of annotations upfront can be challenging. We offer flexibility in such cases:.

Transparency and Communication

To ensure a smooth and collaborative process we aim for clear communication, centralized information management, and the flexibility to adapt to the specific needs of your project:

Annotation Package - Option 1 (Range 0 to 10k)
For 0 to 10k annotations of image classification there is no per annotation option, no matter the size, 100$ should be paid in full for each batch that you order.
Annotation Package - Option 2 (Range 10k to 50k)
For 10k to 50k annotations of image classification we use 0.01 per annotation option, at first 100$ should be paid before we initiate the work. Remaining should be paid after the work is done.
Annotation Package - Option 3 (Range 50k to 200k)
For 50k to 200k annotations of image classification we use 0.01 per annotation option, at first 500$ should be paid before we initiate the work. Remaining should be paid after the work is done.
Annotation Package - Option 4 (Range 200k to 400k)
For 200k to 400k annotations of image classification we use 0.01 per annotation option, at first 2000$ should be paid before we initiate the work. Remaining should be paid after the work is done.
Annotation Package - Option 5 (Range more than 400k)
For more than 400k annotations of image classification we use 0.01 per annotation option, in general you will pay approximately 25% beforehand and after the work is done you will pay the remaining.

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