Cooking State Recognition from Images Using Inception Architecture
A kitchen robot properly needs to understand the cooking environment to continue any cooking activities. But object's state detection has not been researched well so far as like object detection. In this paper, we propose a deep learning approach to identify different cooking states from images for a kitchen robot. In our research, we investigate particularly the performance of Inception architecture and propose a modified architecture based on Inception model to classify different cooking states. The model is analyzed robustly in terms of different layers, and optimizers. Experimental results on a cooking datasets demonstrate that proposed model can be a potential solution to the cooking state recognition problem.
Code (0)
등록된 구현이 없습니다.
Tasks
object-detectionObject DetectionSimilar Papers 제목 키워드 기반
State Classification with CNN
There is a plenty of research going on in field of object recognition, but object state recognition has not been addressed as much. There are many important applications which can utilize object state recognition, such a…
ClassificationGeneral ClassificationObjectObject Recognition+1Tuned Inception V3 for Recognizing States of Cooking Ingredients
Cooking is a task that must be performed in a daily basis, and thus it is an activity that many people take for granted. For humans preparing a meal comes naturally, but for robots even preparing a simple sandwich result…
Transfer LearningCookGAN: Causality Based Text-to-Image Synthesis
This paper addresses the problem of text-to-image synthesis from a new perspective, i.e., the cause-and-effect chain in image generation. Causality is a common phenomenon in cooking. The dish appearance changes depending…
Image GenerationRethinking Cooking State Recognition with Vision Transformers
To ensure proper knowledge representation of the kitchen environment, it is vital for kitchen robots to recognize the states of the food items that are being cooked. Although the domain of object detection and recognitio…
Inductive Biasobject-detectionObject DetectionTransfer LearningContinuous Object State Recognition for Cooking Robots Using Pre-Trained Vision-Language Models and Black-box Optimization
The state recognition of the environment and objects by robots is generally based on the judgement of the current state as a classification problem. On the other hand, state changes of food in cooking happen continuously…