Abstract: A method, an apparatus, an electronic device, and a storage medium for detecting water content in a battery are provided. The method comprises: obtaining a capacitance detection value of a battery to be tested by measurement; and determining a first water content value of the battery to be tested according to the capacitance detection value and a capacitance-water content relationship model. The capacitance-water content relationship model is obtained according to the relationship between sample batteries with different water content values and their sample capacitance values. By pre-constructing the relationship between the water content of the sample battery and the sample capacitance value and determining the water content of the battery to be tested according to the relationship and the capacitance value of the battery to be tested, the step of manually cutting the electrode sheet is reduced, and the efficiency of detecting the water content in the battery is improved.

Abstract: A battery box and a battery pack are provided. The battery box includes a bottom plate and a side wall. The side wall and the bottom plate enclose a space for accommodating a battery and/or an electrical component. The battery box further includes a lifting column integrally formed with the side wall and a fixed sealing block sleeved on the lifting column. The bottom plate is located between the side wall and the fixed sealing block. The side wall is fixedly connected to the bottom plate through the fixed sealing block. A first sealing member for sealing a gap between the fixed sealing block and the bottom plate is arranged between the fixed sealing block and the bottom plate. The fixed sealing block is sealingly connected to the lifting column.

Abstract: A gesture language recognition method is provided. In the method, a first video is obtained. Gesture features are extracted from frames of images in the first video. Gesture change features are extracted from the frames of the images in the first video. Gesture language word information is extracted from fused features that are determined based on the gesture features and the gesture change features. The gesture language word information is combined into a gesture language sentence according to context information corresponding to the gesture language word information.

Abstract: A gesture language recognition method is provided. In the method, a first video is obtained. Gesture features are extracted from frames of images in the first video. Gesture change features are extracted from the frames of the images in the first video. Gesture language word information is extracted from fused features that are determined based on the gesture features and the gesture change features. The gesture language word information is combined into a gesture language sentence according to context information corresponding to the gesture language word information.